The State of Forests Growing on Iron Oxide-Saturated Soils of Azerbaijan
DOI:
https://doi.org/10.37482/0536-1036-2022-6-117-125Keywords:
forest-vegetation cover, mountain forests, satellite images, spectral indices, forest state, minerals, iron oxideAbstract
Today Azerbaijan focuses on the non-oil sector development. The mining industry is actively growing, to become one of its driving forces. This is detrimental to the ecology of the region. The intensive mining activity has become one of the reasons for the mountain forests degradation in the West of the country. The article is devoted to the study of the mutual influence of the forests state and the presence of minerals containing iron oxides in the soil in the Lesser Caucasus region, which involves two industrially developed districts of Azerbaijan: Dashkesan and Gadabay. The study is based on the calculation of spectral indices of satellite
imagery over a significant period of time. The paper shows the processing of satellite images, including their pretreatment, spectral, geospatial and correlation analysis aimed at finding quantitative coefficients of the relationship between the iron oxides fraction in the soil and the forest state. Spectral analysis allows determining the forest state by calculating the SIPI vegetation index, as well as the iron oxide minerals presence in the soils of the region by calculating the Ferric oxides multispectral index. Geospatial analysis is designed to assess the forest state in the areas of these mineral deposits. Correlation analysis is used to compare the degradation processes in the studied districts. There are electronic maps compiled by overlapping the forest state and the iron oxide content maps. There is a dynamics confirming an increase in the share of degraded forests in the areas of research.
For citation: Aliyev B.G., Mamedaliyeva V.M. The State of Forests Growing on Iron Oxide-Saturated Soils of Azerbaijan. Lesnoy Zhurnal = Russian Forestry Journal, 2022, no. 6, pp. 117–125. (In Russ.). https://doi.org/10.37482/0536-1036-2022-6-117-125
Downloads
References
Алиев Б.Г., Алиев И.Н. Проблемы эрозии в Азербайджане и пути ее решения. Баку: Нурлан, 2000. 122 с. Aliyev B.G., Aliyev I.N. Erosion Problems in Azerbaijan and Ways to Solve Them. Baku, Nurlan Publ., 2000. 122 p. (In Russ.).
Бузмаков С.А., Санников П.Ю., Андреев Д.Н. Подготовка и применение материалов аэрофотосъемки для изучения лесов // Изв. Самар. НЦ РАН. 2016. Т. 18, № 2. C. 313–316. Buzmakov S.A., Sannikov P.Yu., Andreev D.N. Preparation and Applying of Aerial Photography for the Forest Studying. Izvestia of Samara Scientific Center of the Russian Academy of Sciences, 2016, vol. 18, no. 2, pp. 313–316. (In Russ.).
Все о геологии. Месторождение Дашкесан. Режим доступа: https://wiki.web.ru/wiki/Месторождение_Дашкесан (дата обращения: 31.10.22). All about Geoplogy. Dashkesan Deposit. (In Russ.).
Горные леса – основа нашего будущего/Продовольственная и сельскохозяйственная организация Объединенных Наций, ФАО. Отдел по оценке, рациональному использованию и сохранению лесов. Режим доступа: http://caresd.net/img/docs/8517.pdf (дата обращения: 31.10.22). Mountain Forests are the Basis of Our Future. Division for Assessment, Rational Use and Conservation of Forests, Food and Agriculture Organization of the United Nations, FAO. (In Russ.).
Дашкесан. Режим доступа: https://portal.azertag.az/ru/node/2598 (дата обращения: 31.10.22). Dashkesan. (In Russ.).
Колесникова О.Н., Черепанов А.С. Возможности ПК ENVI для обработки мультиспектральных и гиперспектральных данных // Геоматика. 2009. № 3. С. 24–27. Kolesnikova O.N., Cherepanov A.S. New ENVI Software Opportunities for Processing Multispectral and Hiperspectral Data. Geomatica, 2009, no. 3, pp. 24–27. (In Russ.).
Химическая классификация минералов. Режим доступа: https://bsu.by/faculties/ekspozitsii-muzeya/khimicheskaya-klassifikatsiya-mineralov.php (дата обращения: 29.11.22). Chemical Classification of Minerals. Belarusian State University. (In Russ.).
Черепанов А.С. Вегетационные индексы // Геоматика. 2011. № 2. C. 98–102. Cherepanov A.S. Vegetation Indices. Geomatica, 2011, no. 2, pp. 98–102. (In Russ.).
Черепанов А.С., Дружинина Е.Г. Спектральные свойства растительности и вегетационные индексы // Геоматика. 2009. № 3. С. 28–32. Cherepanov A.S., Druzhinina E.G. Spectral Properties of Vegetation and Vegetation Indices. Geomatica, 2009, no. 3, pp. 28–32. (In Russ.).
Чухланцев А.А., Саворский В.П. Задачи дистанционного зондирования лесов при изучении глобальных климатических изменений // Современные проблемы дистанционного зондирования Земли из космоса. 2011. Т. 8, № 2. С. 246–256. Chukhlantsev A.A., Savorskij V.P. Remote Sensing of Forests in Context of Global Change. Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa = Current problems in remote sensing of the Earth from space, 2011, vol. 8, no. 2, pp. 246–256. (In Russ.).
Altamirano A., Aplin P., Miranda A., Cayuela L., Algar A.C., Field R. High Rates of Forest Loss and Turnover Obscured by Classical Landscape Measures. Applied Geography, 2013, vol. 40, pp. 199–211. https://doi.org/10.1016/j.apgeog.2013.03.003
Dashkesan Co-Fe Deposit, Dashkesan, Dashkesan District, Azerbaijan. Mindat. Available at: https://www.mindat.org/loc-2780.html (accessed 22.04.21).
Ducart D., Silva A., Toledo C. et al. Mapping Iron Oxides with Landsat-8/OLI and EO-1/Hyperion Imagery from the Serra Norte Iron Deposits in the Carajás Mineral Province, Brazil. Brazilian Journal of Geology, 2016, vol. 46, no. 3, pp. 331–349. https://doi.org/10.1590/2317-4889201620160023
Geology Indices Background. L3Harris. Available at: https://www.l3harrisgeospatial.com/docs/backgroundgeologyindices.html (accessed 22.04.21).
Lausch A., Erasmi S., King D.J., Magdon P., Heurich M. Understanding Forest Health with Remote Sensing – Part I – A Review of Spectral Traits, Processes and Remote-Sensing Characteristics. Remote Sensing, 2016, vol. 8, iss. 12, art. 1029. https://doi.org/10.3390/rs8121029
Lewis S.L., Edwards D.P., Galbraith D. Increasing Human Dominance of Tropical Forests. Science, 2015, vol. 349, iss. 6250, pp. 827–832. https://doi.org/10.1126/science.aaa9932
Mate A.R., Deshmukh R.R. Analysis of Effects of Air Pollution on Chlorophyll, Water, Carotenoid and Anthocyanin Content of Tree Leaves Using Spectral Indices. International Journal of Engineering Science and Computing, 2016, vol. 6, no. 8, pp. 5465–5474.
Nemani R.R., Keeling C.D., Hashimoto H., Jolly W.M., Piper S.C., Tucker C.J., Myneni R.B., Running S.W. Climate-Driven Increases in Global Terrestrial Net Primary Production from 1982 to 1999. Science, 2003, vol. 300, iss. 5625, pp. 1560–1563. https://doi.org/10.1126/science.1082750
Parashar S., Bhatia K., Bhadola S. Image Processing: A Methodology to Detect Plant Diseases. International Journal of Computer Science and Mobile Computing, 2019, vol. 8, iss. 4, pp. 209–216.
Sergieieva K. Spectral Indices to Drive Digital Agri Solutions. EOS Data Analytics. Available at: https://eos.com/blog/vegetation-indices/ (accessed 10.01.22).
